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    <title>regress</title>
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    <div align="right">Last update : February 2001</div>
    <p>
      <b>regress</b> -  regression coefficients of two variables</p>
    <h3>
      <font color="blue">Calling Sequence</font>
    </h3>
    <dl>
      <dd>
        <tt>coefs=regress(x,y)  </tt>
      </dd>
    </dl>
    <h3>
      <font color="blue">Parameters</font>
    </h3>
    <ul>
      <li>
        <tt>
          <b>x,y</b>
        </tt>: real or complex vector</li>
    </ul>
    <h3>
      <font color="blue">Description</font>
    </h3>
    <p>
    This function  computes the regresion  coefficients of two
    variables <tt>
        <b>x</b>
      </tt>  and <tt>
        <b>y</b>
      </tt>, both  numerical vectors of
    same number  of elements  <tt>
        <b>n</b>
      </tt>. <tt>
        <b>coefs=[a b]</b>
      </tt>  be a
    1x2 matrix such that  <tt>
        <b>Y=a+bX</b>
      </tt> will be the equation of
    the ordinary least square approximation to our data.</p>
    <h3>
      <font color="blue">References</font>
    </h3>
    <dl>
      <p>
    Wonacott, T.H. &amp; Wonacott, R.J.; Introductory Statistics, J.Wiley &amp; Sons, 1990.</p>
    </dl>
    <h3>
      <font color="blue">Examples</font>
    </h3>
    <pre>

x=[0.5608486 0.6623569 0.7263507 0.1985144 0.5442573 0.2320748 0.2312237]
y=[0.3616361 0.2922267 0.5664249 0.4826472 0.3321719 0.5935095 0.5015342]
coefs=regress(x,y)
 
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    <h3>
      <font color="blue">See Also</font>
    </h3>
    <p>
      <a href="covar.htm">
        <tt>
          <b>covar</b>
        </tt>
      </a>,&nbsp;&nbsp;</p>
    <h3>
      <font color="blue">Author</font>
    </h3>
    <p> Carlos Klimann</p>
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